Bio-mesh network leveraging natural selection optimization for intelligent auto-healing

ABSTRACT

Apparatus and methods for accelerating the remediation of broken transactions using parallel machine learning processing and optimization is provided. The methods may include a network access point receiving, from an application programming interface, a broken transaction. The methods may also include a network access point selecting a bionic element within a bio-mesh network for processing the broken transaction and routing the broken transaction to the bionic element. The bio-mesh network may include a plurality of bionic elements. The methods may further include the bionic element receiving the broken transaction and extracting, from the broken transaction, a set of features, transmitting the set of features to a policy bank, and, in response to the policy bank failing to identify a stored routine associated with the set of features for fixing the broken transaction, running in parallel two machine-learning algorithms to identify an optimal routine for fixing the broken transaction.

FIELD OF TECHNOLOGY

Aspects of the disclosure relate to fixing broken transactions. Inparticular, aspects of the disclosure relate to leveraging naturalselection optimization to fix broken transactions in a muti-tiernetwork.

BACKGROUND

The successful capture of a trade within a trading system should resultin the trade details being sent to the back office immediately, via aninterface, for operational processing. If any trade details are not fedto a downstream System of Records, an operations team needs toinvestigate the broken transaction and determine how to fix the breaksor flow. However, manual identification and investigation of crosstrading platform broken transactions cannot provide near real timeremediation. The resultant time lag in fixing the broken transaction canresult in numerous reconciliation difficulties, such as businessescalation, reputational risk and SLA miss for reconciliation.

It would be desirable, therefore, to provide systems and methods forauto healing a broken transaction in real time, to avoid missingreconciliation deadlines and to enhance performance and customerrelations.

BRIEF DESCRIPTION OF THE DRAWINGS

The objects and advantages of the disclosure will be apparent uponconsideration of the following detailed description, taken inconjunction with the accompanying drawings, in which like referencecharacters refer to like parts throughout, and in which:

FIG. 1 shows illustrative apparatus and methods in accordance with theinvention;

FIG. 2 shows an illustrative apparatus and methods in accordance withthe invention;

FIG. 3 shows an illustrative apparatus and methods in accordance withthe invention;

FIG. 4 shows illustrative block diagram of apparatus in accordance withthe invention; and

FIG. 5 shows illustrative apparatus that may be configured in accordancewith the invention.

DETAILED DESCRIPTION

Apparatus and methods for accelerating the remediation of brokentransactions using parallel machine learning processing and optimizationare provided. The methods may include method steps performed by one ormore of a network access point, an application programming interface(“API”), a gateway cache, a bionic element, a policy bank and/or a datastore as described herein.

For the purposes of the application, a transaction may be a financialtransaction characterized by one or more electronic entries into a bank,brokerage house, stock trading platform, or any other suitable location.As a transaction is electronically processed by a processing entity suchas a bank, or a clearing house, an entry may be created in a header ofthe transaction. Exemplary information input into a header of atransaction each time the transaction is processed may include abusiness identifier identifying the business that is processing thetransaction, the processing that has been applied to the transaction, adebit and corresponding credit, a key created by the processing entity,a timestamp, and any other suitable data.

For each transaction, there may be systems in place that must be adheredto which, if not followed, characterize a transaction as ‘broken.’ Forexample, for every debit executed by a processing entity when processingthe transaction, there must be a stored, corresponding credit, and viceversa. As such, if a transaction includes an entry that is missing acounter entry - e.g. because the entry is carrying a different amount, adifferent description of posted entry, or the entry is not available -this transaction may then be classified as a broken transaction. Otherexamples of a broken transaction may include a transaction that wentthrough a processing step but the associated data is missing in theheader, a transaction having an entry with an incorrect value date -i.e., an incorrect timestamp, such as when there is a mismatch between atimestamp appended to the sender of the transaction and a timestampappended to a receiver of the transaction, whether or not a processexecuted on the transaction has an associated stored key, etc.

The methods may include the network access point receiving, from anapplication programming interface (“API”), a broken transaction. It isto be understood that the network access point may receive brokentransactions from two or more APIs.

The methods may include the network access point selecting a bionicelement within a bio-mesh network for processing the broken transaction.The network access point may route the broken transaction to theselected bionic element.

The bio-mesh network may include a plurality of bionic elements. Eachbionic element have similar or different processing capabilities. Thenetwork access point may maintain a queuing table used to determinewhich bionic element should accept a broken transaction. In someembodiments, a gateway cache may maintain the queuing table.

In some embodiments, the methods may include a gateway cache storing alog recording the routing of broken transactions from the network accesspoint to the plurality of bionic elements. The methods may also includethe gateway cache maintaining a prioritization algorithm used by thenetwork access point to determine which bionic element in the pluralityof bionic elements should receive an incoming broken transaction. Inexemplary embodiments, the gateway cache may store data detailing, foreach bionic element, a quantity of transactions that each bionic elementcan handle. The prioritization algorithm may be used to prioritize afirst bionic element over a second bionic element based, for example, onprocessing speed, a strength of a network connection, past performance,or any other suitable factors.

The methods may include the bionic element receiving the brokentransaction. The methods may include the bionic element extracting fromthe broken transaction a set of features. The set of features may bestored in a header of the broken transaction. The set of features mayinclude one or more of an account time stamp, a transaction type, atransaction amount, a transaction time stamp, an origin account and adestination account.

The methods may include the bionic element transmitting the set offeatures to a policy bank. When bionic element determines that thepolicy bank stores data corresponding to the set of features andadditionally stores a routine for fixing a transaction having the set offeatures, the bionic element may transmit the routine to the policyapplication pipeline for implementing the routine.

In response to the policy bank failing to identify a stored routineassociated with the set of features for fixing the broken transaction,the methods may include the bionic element identifying, from a header ofthe broken transaction, each instance of the transaction being processedby a processing entity. The methods may also include the bionic elementassigning to each instance, in chronological order, a step number, torepresent the transaction as a sum of n_(x) steps from x=0 to x=n. Themethods may also include the bionic element associating with each n_(x)step information stored in the header for that n_(x) step. Theconversion of the transaction into a set of consecutive numerical stepswith associated data may enable the machine learning algorithmsdiscussed below to process the transaction data.

The methods may include the bionic element, for each step, comparinginformation stored in the header associated with the step to complianceprotocols. Exemplary compliance protocols may include a match between adebit entry and a corresponding credit entry, a correct value date andeach step being step associated with a key.

In some embodiments, the methods may include the bionic elementidentifying, based on information stored in the header, one or moreerrors in a subset of the n steps. Each error may include one or more ofa mismatch between a debit entry and a corresponding credit entry, anincorrect value date and/or a failure to be associated with a key. Theerrors may be a failure of the data associated with the step to conformto the compliance protocols.

The methods may include the bionic element identifying a subset of thesteps that fail to satisfy one or more of the compliance protocols. Themethods may include the bionic element feeding the sequence of steps,the subset of the steps, and, for each step in the subset, informationdetailing the one or more failures to meet the compliance protocols, toboth a firefly algorithm (“FI”) and a genetic algorithm (“GA”).Alternately, the methods may include the bionic element feeding thesequence of steps, the subset of the steps, and, for each step in thesubset, the errors identified, to both the firefly algorithm (“FI”) andthe genetic algorithm (“GA”).

The methods may include the bionic element running the FI and GA, inparallel. The methods may include the bionic element receiving from theFI and GA outputs including, for each step in the subset, one or moresolutions. The methods may include the bionic element using anoptimization algorithm set to optimize speed only, selecting from theoutputs of the FI and GA, for each step, a first optimized solution. Theoptimization algorithm may use derivatives or may not using derivatives.The optimization algorithm may use first and/or second derivatives of anobjective function, or any other suitable optimization algorithm.Exemplary optimization algorithms may include an adaptive learning ratemodel, a gradient descent method, a stochastic gradient descent, or anyother suitable optimization algorithm. The methods may include thebionic element combining each first optimized solution, of each step, tocreate a first policy. The methods may include the bionic elementtransmitting the first policy to a policy application pipeline.

The methods may include the policy application pipeline implementing thefirst policy to the broken transaction to convert the broken transactionto a first fixed transaction and transmitting the first fixedtransaction to the network access point. The policy application pipelinemay first look for any specific protocols or business logics associatedwith the API that sent out the broken transaction. These specificprotocols or business logics may first be applied to the transaction.Once these are accounted for, the first policy may be applied to thebroken transaction. Exemplary business logics may include each entry inthe transaction storing the value data in decimals and not in acents/dollar format. An exemplary policy for fixing a broken transactionmay include re-routing the transaction to one of the processing entitiesto re-process the transaction at that step where there was a failure,and then passing the transaction through the remaining steps because thefailure at the processing entity cascaded to the remaining entities thatprocessed the transaction. The re-processing may include an instructionto the processing entity to include a counter-entry of a debit/creditthat was mistakenly omitted previously.

The methods may include the network access point transmitting the firstfixed transaction to the API. The methods may include the network accesspoint, prior to transmitting the first fixed transaction to the API,searching a log file stored in a gateway cache to retrieve acommunication protocol associated with the API.

The methods may include the network access point, in response to thetransmission, receiving a response from the API indicating that thefirst fixed transaction has been rejected. The API may reject the firstfixed transaction based on one or more user-specific rules stored in theAPI. The API may be referred to alternately herein as a ‘user.’ Forexample, the API may be run by a brokerage house, a hedge fund, a bank,a line of business within a bank, or any other suitable user. The APImay store, or access stored, user-specific rules listing features that atransaction must have for the transaction to be accepted by the user. A‘fixed’ transaction that does not satisfy the user-specific rules may berejected by the user and a message indicating the rejection may betransmitted by the API back to the network access point.

In some embodiments, the API may transmit back to the network accesspoint a binary response - such as ‘fixed’ or ‘not fixed’, ‘acceptable’or ‘not acceptable’, etc., to indicate whether or not the transactionhas been accepted by the user’s system. Thus, the response received bythe network access point from the API may not detail what aspects of thetransaction were rejected. In these embodiments, the bionic elementmust, on its own, figure out a new policy to fix the transaction withoutany feedback from the user’s system that rejected the first fixedtransaction.

The methods may include the network access point transmitting a commandto the bionic element to output a second policy to fix the brokentransaction. In response to receipt of the command, the methods mayinclude the bionic element adjusting the optimization algorithm tooptimize both speed and accuracy. The methods may include the bionicelement, using the adjusted optimization algorithm, to select from thepreviously-output outputs of the FI and GA, a second optimized solutionfor each step included in the subset. The methods may include the bionicelement combining each second optimized solution to create a secondpolicy. The methods may include the bionic element transmitting thesecond policy to the policy application pipeline.

The methods may include the policy application pipeline implementing thesecond policy to the broken transaction to convert the brokentransaction to a second fixed transaction and transmit the second fixedtransaction to the network access point.

The methods may include the network access point performing the methodsteps of transmitting the second fixed transaction to the API. Themethods may include the network access point, in response to thetransmission, receiving a response from the API indicating that thesecond fixed transaction has been accepted. The response may be a binaryresponse as described above.

The methods may include the network access point, in response to thereceipt of the response from the API indicating that the second fixedtransaction has been accepted, transmitting an instruction to the bionicelement to upload to the policy bank the set of features and the secondpolicy.

The methods may include the bionic element, in response to receipt ofthe instruction, uploading to the policy bank the set of features andthe second policy. The uploading, by the bionic element, of the set offeatures and the second policy may augment the policy bank’s data storeto include the newly-developed second policy that successfully fixed thebroken transaction having the set of features.

The methods may include the network access point, in response to thetransmission, receiving a response from the API indicating that thesecond fixed transaction has been rejected. In response, the networkaccess point may transmit an instruction to the bionic element to fixthe broken transaction again. In response, the bionic element may adjustthe optimization algorithm to optimize accuracy more than was optimizedwhen creating the second policy, and to optimize speed less than wasoptimized when creating the second policy. The optimization algorithmmay then be used to create a third policy using the method stepsdescribed above with respect to the second policy. As such, it followsthat as a broken transaction is rejected one, two, three, four, or moretimes by an API, the bionic element may, each time, incrementallyincrease the prioritization of optimizing the accuracy of the solutionand incrementally decrease the prioritization of optimizing the speed atwhich the solution is output. After the rejection of a brokentransaction more than a threshold number of times by an API, the brokentransaction may be transmitted to a queue for being manually solved.

Methods performed by the bionic element may be performed by some or allof the bionic elements in the bio-mesh network. As such, each bionicelement in the bio-mesh network may receive broken transactions andexecute the methods described herein to fix the broken transactions.Specifically, prior to processing a broken transaction using artificialintelligence and machine learning, each bionic element may first checkthe policy bank to see if a broken transaction having the set offeatures of the current broken transaction was previously fixed. If sucha policy has already been created, the bionic element may implement thepreviously-generated policy, thus avoiding the need to process thetransaction using the artificial intelligence (“AI”) methods of theparallel processing of the GA and FI algorithms. It follows that thecollective intelligence provided by the bio-mesh system provides that asolution generated by one bionic element is subsequently available, viathe policy bank, to all bionic elements to use. This may allow for thequick fixing of broken transactions using the stored policy data andfrees up the computational resources of all the bionic elements toprocess only broken transactions that have not yet been fixed by adifferent bionic element in the bio-mesh network.

In some embodiments, when the bionic element is a first bionic elementand the broken transaction is a first broken transaction, the methodsmay include the gateway cache maintaining a log of each transactionbeing processed by bionic elements in the bio-mesh network. The methodsmay include each bionic element in the bio-mesh network transmittingdata to the gateway after receiving a broken transaction for processing,the data including the transaction and/or the set of features. When atransaction has been fixed, the network access point may notify thegateway cache to delete information relating to the transaction from thelog.

The bionic element may be a first bionic element, and the brokentransaction may be a first broken transaction. In some of theseembodiments, the methods may include the first bionic element searchingthe gateway cache to determine if a second bionic element included inthe bio-mesh network is currently processing a second broken transactionhaving features similar to features of the first broken transaction. Thefirst bionic element may execute these steps after receiving acommunication from the policy bank that there are no stored policysolutions to the broken transactions. The similarity may be set to apre-stored percentage similarity, such as, for example, 60% similar, 70%similar, 80% similar, 90% similar, or any other suitable percentage.

If the gateway cache does not identify a second broken transactioncurrently being processed with the pre-stored percentage similarity, thefirst bionic element may proceed to process the first broken transactionas detailed herein. If the gateway cache does identify a second brokentransaction currently being processed by a second bionic element, thesecond broken transaction having the pre-stored similarity, the firstbionic element may put on hold the processing of the first brokentransaction and begin to process a third broken transaction receivedfrom the network access point. Upon receipt of a message from thegateway cache that the second broken transaction has been fixed, thefirst bionic element may proceed to pull from the policy bank the policyused by the second bionic element to fix the second transaction. If theAPI that generated the first broken transaction accepts that fix, thenthe processing of the first broken transaction by the first bionicelement may have been successfully avoided. If the API that generatedthe first broken transaction sends back a message that the fix has beenrejected, the first bionic element may proceed to process the firstbroken transaction using the AI methods described herein.

In some embodiments, after the running of the FI and GA, in parallel,the methods may include the bionic element combining the outputs of theFI and GA to create all possible solution sets using the outputsolutions. Each solution set may include, for each step in the subset,one of the output solutions. The methods may include, the bionic elementusing an optimization algorithm, selecting from the solution sets themost optimal solution set, the second-most optimal solution set, and thethird-most optimal solution step. The methods may further include thebionic element transmitting to a policy application pipeline the mostoptimal solution set, the second-most optimal solution set, and thethird-most optimal solution set. In some embodiments, four solutionssets, five solution sets, or more may be transmitted to the policyapplication pipeline.

The methods may also include the policy application pipelineimplementing the most optimal solution set to the broken transaction toconvert the broken transaction to a first fixed transaction and transmitthe first fixed transaction to the network access point. If the firstfixed transaction is rejected by the API, the methods may include thenetwork access point transmitting a command to policy applicationpipeline to fix the broken transaction.

The methods may include the policy application pipeline for implementingthe second-most optimal solution set to the broken transaction toconvert the broken transaction to a second fixed transaction andtransmit the second fixed transaction to the network access point. Themethods may further include the network access point transmitting thesecond fixed transaction to the API, in response to the transmission,receiving a response from the API indicating that the second fixedtransaction has been accepted, and transmitting an instruction to thepolicy application pipeline to upload to the policy bank the set offeatures and the second-most optimal solution set.

If the network access point receives from the API a response indicatingthat the second fixed transaction has been rejected, the methods mayinclude the network access point transmitting an instruction to thepolicy application pipeline to fix the broken transaction. The policyapplication pipeline may immediately implement the third-most optimalsolution set to fix the transaction. As such, consecutive optimizedsolution models may be applied to fix the broken transaction withouthaving to re-run the optimization algorithm.

Illustrative embodiments of apparatus and methods in accordance with theprinciples of the invention will now be described with reference to theaccompanying drawings, which form a part hereof. It is to be understoodthat other embodiments may be utilized, and structural, functional andprocedural modifications may be made without departing from the scopeand spirit of the present invention.

The drawings show illustrative features of apparatus and methods inaccordance with the principles of the invention. The features areillustrated in the context of selected embodiments. It will beunderstood that features shown in connection with one of the embodimentsmay be practiced in accordance with the principles of the inventionalong with features shown in connection with another of the embodiments.

Apparatus and methods described herein are illustrative. Apparatus andmethods of the invention may involve some or all of the features of theillustrative apparatus and/or some or all of the steps of theillustrative methods. The steps of the methods may be performed in anorder other than the order shown or described herein. Some embodimentsmay omit steps shown or described in connection with the illustrativemethods. Some embodiments may include steps that are not shown ordescribed in connection with the illustrative methods, but rather shownor described in a different portion of the specification.

One of ordinary skill in the art will appreciate that the steps shownand described herein may be performed in other than the recited orderand that one or more steps illustrated may be optional. The methods ofthe above-referenced embodiments may involve the use of any suitableelements, steps, computer-executable instructions, or computer-readabledata structures. In this regard, other embodiments are disclosed hereinas well that can be partially or wholly implemented on acomputer-readable medium, for example, by storing computer-executableinstructions or programs or by utilizing computer-readable datastructures.

FIG. 1 shows illustrative apparatus, system architecture and methods inaccordance with the invention. In FIG. 1 , user 117, user 119 and user121 are shown communicating with network access point 113 via internetconnection 115. Each user may be an API and perform the associated APIfunctions described herein. A user may be a hedge fund, retail banking aline of business within a bank, a bank, or any other suitable entity.Each of user 117, user 119 and user 121 may use transaction processingservices provided by a transaction processing entity. The transactionprocessing entity may run network access point 113, gateway cache 123,bio-mesh network 104 including bionic elements 102 a-h, policy bank 109,data stored 11 and GPU acceleration 103. For example, user 117 maytransmit to the transaction processing entity a transaction forprocessing. The network access point 113 may transmit back to user 117the transaction once the processing of the transaction has beencompleted.

Network access point 113 may receive from one or more of user 117, user119 and user 121, a data packet including a transaction. The data packetmay include information indicating that the transaction included in thedata packet has been rejected, such as a line of code, a flag, or anyother suitable information. A rejected transaction may be referred toalternately herein as a ‘broken transaction.’ Network access point 113may proceed to route the broken transaction for remediation to bio-meshnetwork 104 for remediation as described herein. Gateway cache 123 maystore data relating to all details of the communications between networkaccess point 113 and bio-mesh network 104. This may provide networkaccess point 113 with stored knowledge relating to which transaction wasrouted to which bionic element.

A fixed transaction may be received by network access point 113 from abionic element. Network access point 113 may then route the fixedtransaction to the one of users 117, 119 and 121, from which thetransaction was originally received.

If the user receiving the transaction determines that the fixedtransaction is not properly fixed as per one or more rules stored in adatabase of the user, the user may route a first binary response tonetwork access point 113. The first binary response may be ‘rejected’,or any other suitable response indicating that the fixed transaction isunacceptable to the user. Network access point 113 may then check withgateway cache 123 to determine which bionic element was responsible forfixing the transaction most recently received from the user. Uponidentification of a bionic element, network access point 113 may thenroute the transaction to the identified bionic element to execute anadditional attempt fix the transaction, as described herein.

If the user receiving the transaction determines that the fixedtransaction is acceptable, the user may transmit a second binaryresponse to network access point 113 indicating that the transaction wasfixed. The second binary response may be ‘accepted’ or any othersuitable response indicating that the fixed transaction is acceptable tothe user. Upon receipt of the second binary response, network accesspoint may check gateway cache 123 to determine which bionic element wasresponse for fixing the transaction most recently received from the userand, after identification, route an instruction to the bionic element toupload to policy bank 109 details regarding the broken transaction thatthe bionic element fixed, together with the remedial action taken by thebionic element to fix the transaction.

Bio-mesh network 104 may be in electronic communication with policy bank109 and data store 111. Policy bank 109 may store historical records ofbroken transactions and, for each stored broken transaction, one or moreremedial steps taken to fix the broken transaction. Policy bank 109 mayalso store one or more user-specific rules that must be applied whenfixing a broken transaction originating from one of the users.

Data store 111 may store historical records of broken transactions and,for each stored broken transaction, a policy including one or moreremedial steps taken to fix the broken transaction. This may provideredundancy for the data stored in policy bank 109. Data store mayadditionally store each transaction log’s references, either as a copyof the data itself or only the log reference, and the transaction’sfeatures. Data stored on the data store may be encrypted and/oranonymized based on requirement protocols. For example, in someembodiments, each bionic element may transmit to data store 111 featuresof a broken transaction being processed immediately upon receipt. When abionic element receives a second binary response from network accesspoint 113 indicating that a broken transaction has been fixed, thebionic element may transmit an instruction to data store 111 to purgedata relating to the now-fixed transaction.

Bio-mesh network 104 may run on GPU acceleration 103, which may includehardware 105 and software 107. GPU acceleration 103 may include one ormore features of apparatus illustrated in FIGS. 4 and 5 .

FIG. 2 shows broken transaction 201 being fed to bionic element 102 aand being output from bionic element 102 a as fixed transaction 231.Broken transaction 201 may be routed to bionic element 102 a fromnetwork access point 113.

Bionic element 102 a may include controller 203 and optimizer 213.Bionic element 102 a may be powered by GPU acceleration 103, asdiscussed in FIG. 1 .

Broken transaction 201 may be received by controller 203. In controller203, broken transaction 201 may be initially fed to feature extractor205. Feature extractor 205 may extract features of broken transaction201. The extracted features may be the set of features. Featureextractor 205 may transmit the extracted features to data store 111, toupdate the cache in data store 111 relating to the current transactionsbeing processed by the bionic elements included in bio-mesh network 104.

Feature extractor 205 may transmit the features to classifier pipeline207. Classifier pipeline 207 may communicate with policy bank 109 viademux 209 and policy application pipeline 211 to determine if thefeatures of broken transaction 201 are stored in policy bank 109. If thefeatures are present, classifier pipeline 207 may then determine ifpolicy bank 109 has stored policies for how to remediate the features.If it does, bionic element 102 a may extract the policies, instructpolicy application pipeline 211 to implement them, and then output fixedtransaction 231 to network access point 113.

If the features are not present in policy bank 109, or if the featuresare present but there is no associated policy for how to fix thefeatures, classifier pipeline and/or feature extractor 205 may transmitthe features to optimizer 213. Feature 2 particle initializer 215 mayreceive the features. Feature 2 particle initializer may further breakdown the broken transaction into smaller sub-features as discussedherein.

The smaller sub-features may be fed in parallel to two machine learningalgorithms, such as Firefly Intelligence and Genetic Algorithm.Specifically, the smaller sub-features may be fed in parallel toparticle generation using firefly intelligence 223 and particlegeneration using genetic algorithm 225 to output ‘particles’ - i.e.solution sets for the broken transaction. An optimization algorithm,such as natural selection of best fit through elimination 227, may thenbe used to take the solutions output by each of the genetic algorithmsand select which of solution set is optimal, as discussed herein.

The optimal solution set may be transmitted to policy applicationpipeline 211. Policy application pipeline may apply the optimal solutionset to broken transaction 201 to generate fixed transaction 231. Fixedtransaction 231 may then be transmitted back to the user for which thetransaction was originally generated. If the user transmits a secondbinary response to network access point 113 indicating that fixedtransaction 231 failed to meet one or more of the user’s internalrequirements for an acceptable transaction, bionic element 102 a mayreceive a message from network access point 113 to execute a second fixto the transaction. Bionic element 102 a may then update itsoptimization rules and then update the best fit 229. Based on theupdated optimization rules, a new set of solutions may be identified asa new optimized solution set. The new set of solutions may betransmitted to policy application pipeline 211, which may apply the newset of solutions to broken transaction 201 and transmit the updatedtransaction back to the user for validation.

Firefly intelligence 217 and genetic algorithm 219 may generate multiplesolutions to solve each step of the broken transaction. Fireflyintelligence 217 and genetic algorithm 219 may also update theiroptimization algorithm for a new solution generation when the networkaccess points receives feedback from a user that a previous fix appliedwas rejected. Upon the generation of a solution policy, distribution ofrules in search area 221 may use the positional velocities of eachproposed solution (obtained from 217 and 219) in the ranges that arerandomly initialized. Updating the best fit 229 may hold the best ‘n’numbers of optimal solutions. This data may be transmitted to fireflyintelligence 217 and, in some embodiments, genetic algorithm 219 forupdating the strategy. This may act as a learning parameter if aproposed policy solution is rejected.

FIG. 3 shows optimizer 213 together with exemplary illustrationsillustrating rule updating with firefly intelligence 217, rules updatingusing genetic algorithm 210, distribution of rules in search area 221,particle generation using firefly intelligence 223, particle generationusing genetic algorithm 225, natural selection of best fit throughelimination 227, and updating the best fit 229. It is to be understoodthat the illustrations in FIG. 3 are for illustrative purposes only, anddo not limit the decisioning processes in any way.

FIG. 4 shows an illustrative block diagram of system 400 that includescomputer 401. Computer 401 may alternatively be referred to herein as an“engine,” “server” or a “computing device.” Computer 401 may be aworkstation, desktop, laptop, tablet, smart phone, or any other suitablecomputing device. Elements of system 400, including computer 401, may beused to implement various aspects of the systems and methods disclosedherein. Each of the apparatus illustrated in FIGS. 1, 2 and 3 ,including users 117, 119 and 121, network access point 113, gatewaycache 123, policy bank 109, data store 111, bio-mesh network 104 and GPUacceleration 103, may include some or all of the elements and apparatusof system 400.

Computer 401 may have a processor 403 for controlling the operation ofthe device and its associated components, and may include RAM 405, ROM407, input/output circuit 409, and a non-transitory or non-volatilememory 415. Machine-readable memory may be configured to storeinformation in machine-readable data structures. The processor 403 mayalso execute all software running on the computer-e.g., the operatingsystem and/or voice recognition software. Other components commonly usedfor computers, such as EEPROM or Flash memory or any other suitablecomponents, may also be part of the computer 401.

The memory 415 may be comprised of any suitable permanent storagetechnology-e.g., a hard drive. The memory 415 may store softwareincluding the operating system 417 and application(s) 419 along with anydata 411 needed for the operation of computer 401. Memory 415 may alsostore videos, text, and/or audio assistance files. The data stored inMemory 415 may also be stored in cache memory, or any other suitablememory.

Input/output (“I/O”) module 409 may include connectivity to amicrophone, keyboard, touch screen, mouse, and/or stylus through whichinput may be provided into computer 401. The input may include inputrelating to cursor movement. The input/output module may also includeone or more speakers for providing audio output and a video displaydevice for providing textual, audio, audiovisual, and/or graphicaloutput. The input and output may be related to computer applicationfunctionality.

Computer 401 may be connected to other systems via a local area network(LAN) interface 413. Computer 401 may operate in a networked environmentsupporting connections to one or more remote computers, such asterminals 441 and 451. Terminals 441 and 451 may be personal computersor servers that include many or all of the elements described aboverelative to computer 401. The network connections depicted in FIG. 4include a local area network (LAN) 425 and a wide area network (WAN)429, but may also include other networks. When used in a LAN networkingenvironment, computer 401 is connected to LAN 425 through a LANinterface 413 or an adapter. When used in a WAN networking environment,computer 401 may include a modem 427 or other means for establishingcommunications over WAN 429, such as Internet 431. Connections betweenComputer 401 and Terminals 451 and/or 441 may be used for connectionsbetween network access point and users 117, 119 and 121, and, in someembodiments, between network access point 113 and bio-mesh network 104.

It will be appreciated that the network connections shown areillustrative and other means of establishing a communications linkbetween computers may be used. The existence of various well-knownprotocols such as TCP/IP, Ethernet, FTP, HTTP and the like is presumed,and the system can be operated in a client-server configuration topermit retrieval of data from a web-based server or API. Web-based, forthe purposes of this application, is to be understood to include acloud-based system. The web-based server may transmit data to any othersuitable computer system. The web-based server may also sendcomputer-readable instructions, together with the data, to any suitablecomputer system. The computer-readable instructions may be to store thedata in cache memory, the hard drive, secondary memory, or any othersuitable memory.

Additionally, application program(s) 419, which may be used by computer401, may include computer executable instructions for invokingfunctionality related to communication, such as e-mail, Short MessageService (SMS), and voice input and speech recognition applications.Application program(s) 419 (which may be alternatively referred toherein as “plugins,” “applications,” or “apps”) may include computerexecutable instructions for invoking functionality related to performingvarious tasks. Application programs 419 may utilize one or morealgorithms that process received executable instructions, perform powermanagement routines or other suitable tasks. Application programs 419may utilize one or more decisioning processes used by one or both of themachine learning algorithms as detailed herein.

Application program(s) 419 may include computer executable instructions(alternatively referred to as “programs”). The computer executableinstructions may be embodied in hardware or firmware (not shown). Thecomputer 401 may execute the instructions embodied by the applicationprogram(s) 419 to perform various functions.

Application program(s) 419 may utilize the computer-executableinstructions executed by a processor. Generally, programs includeroutines, programs, objects, components, data structures, etc. thatperform particular tasks or implement particular abstract data types. Acomputing system may be operational with distributed computingenvironments where tasks are performed by remote processing devices thatare linked through a communications network. In a distributed computingenvironment, a program may be located in both local and remote computerstorage media including memory storage devices. Computing systems mayrely on a network of remote servers hosted on the Internet to store,manage, and process data (e.g., “cloud computing” and/or “fogcomputing”).

Any information described above in connection with data 411, and anyother suitable information, may be stored in memory 415. One or more ofapplications 419 may include one or more algorithms that may be used toimplement features of the disclosure comprising the processing androuting of data packets transmitted to local user zone 101 fromapplications outside local user zone 101.

The invention may be described in the context of computer-executableinstructions, such as applications 419, being executed by a computer.Generally, programs include routines, programs, objects, components,data structures, etc., that perform particular tasks or implementparticular data types. The invention may also be practiced indistributed computing environments where tasks are performed by remoteprocessing devices that are linked through a communications network. Ina distributed computing environment, programs may be located in bothlocal and remote computer storage media including memory storagedevices. It should be noted that such programs may be considered, forthe purposes of this application, as engines with respect to theperformance of the particular tasks to which the programs are assigned.

Computer 401 and/or terminals 441 and 451 may also include various othercomponents, such as a battery, speaker, and/or antennas (not shown).Components of computer system 401 may be linked by a system bus,wirelessly or by other suitable interconnections. Components of computersystem 401 may be present on one or more circuit boards. In someembodiments, the components may be integrated into a single chip. Thechip may be silicon-based.

Terminal 451 and/or terminal 441 may be portable devices such as alaptop, cell phone, Blackberry ®, tablet, smartphone, or any othercomputing system for receiving, storing, transmitting and/or displayingrelevant information. Terminal 451 and/or terminal 441 may be one ormore user devices. Terminals 451 and 441 may be identical to computer401 or different. The differences may be related to hardware componentsand/or software components.

The invention may be operational with numerous other general purpose orspecial purpose computing system environments or configurations.Examples of well-known computing systems, environments, and/orconfigurations that may be suitable for use with the invention include,but are not limited to, personal computers, server computers, hand-heldor laptop devices, tablets, and/or smart phones, multiprocessor systems,microprocessor-based systems, cloud-based systems, programmable consumerelectronics, network PCs, minicomputers, mainframe computers,distributed computing environments that include any of the above systemsor devices, and the like.

FIG. 5 shows illustrative apparatus 500 that may be configured inaccordance with the principles of the disclosure. Apparatus 500 may be acomputing device. Apparatus 500 may include one or more features of theapparatus shown in FIG. 4 . Apparatus 500 may include chip module 502,which may include one or more integrated circuits, and which may includelogic configured to perform any other suitable logical operations.

Apparatus 500 may include one or more of the following components: I/Ocircuitry 504, which may include a transmitter device and a receiverdevice and may interface with fiber optic cable, coaxial cable,telephone lines, wireless devices, PHY layer hardware, a keypad/displaycontrol device or any other suitable media or devices; peripheraldevices 506, which may include counter timers, real-time timers,power-on reset generators or any other suitable peripheral devices;logical processing device 508, which may compute data structuralinformation and structural parameters of the data; and machine-readablememory 510.

Machine-readable memory 510 may be configured to store inmachine-readable data structures: machine executable instructions,(which may be alternatively referred to herein as “computerinstructions” or “computer code”), applications such as applications419, signals, and/or any other suitable information or data structures.

Components 502, 504, 506, 508 and 510 may be coupled together by asystem bus or other interconnections 512 and may be present on one ormore circuit boards such as circuit board 520. In some embodiments, thecomponents may be integrated into a single chip. The chip may besilicon-based.

Thus, systems and methods for the intelligent auto-healing of brokentransactions are provided. Persons skilled in the art will appreciatethat the present invention can be practiced by other than the describedembodiments, which are presented for purposes of illustration ratherthan of limitation.

What is claimed is:
 1. A method for accelerating the remediation ofbroken transactions using parallel machine learning processing andoptimization, the method comprising: a network access point receiving,from an application programming interface (“API”), a broken transaction;the network access point for selecting a bionic element within abio-mesh network for processing the broken transaction and routing thebroken transaction to the bionic element; the bionic element for:receiving the broken transaction and extracting, from the brokentransaction, a set of features; transmitting the set of features to apolicy bank; in response to the policy bank failing to identify a storedroutine associated with the set of features for fixing the brokentransaction: identifying, from a header of the broken transaction, eachinstance of the transaction being processed by a processing entity;assigning to each instance, in chronological order, a step number, torepresent the transaction as a sum of n_(x) steps from x=0 to x=n; foreach step, comparing information stored in the header associated withthe step to compliance protocols; identifying a subset of the steps thatfail to satisfy one or more of the compliance protocols; feed thesequence of steps, the subset of the steps, and, for each step in thesubset, information detailing the one or more failures to meet thecompliance protocols, to both a firefly algorithm (“FI”) and a geneticalgorithm (“GA”); run the FI and GA, in parallel, and receive from theFI and GA outputs including, for each step in the subset, one or moresolutions; using an optimization algorithm set to optimize speed only,selecting from the outputs of the FI and GA, for each step, a firstoptimized solution; combining each first optimized solution to create afirst policy; transmit the first policy to a policy applicationpipeline; the policy application pipeline for implementing the firstpolicy to the broken transaction to convert the broken transaction to afirst fixed transaction and transmit the first fixed transaction to thenetwork access point; the network access point for: transmitting thefirst fixed transaction to the API; in response to the transmission,receiving a response from the API indicating that the first fixedtransaction has been rejected; transmitting a command to the bionicelement to output a second policy to fix the broken transaction; thebionic element for: adjusting the optimization algorithm to optimizeboth speed and accuracy; using the adjusted optimization algorithm,selecting from the outputs of the FI and GA, for each step, a secondoptimized solution; combining each second optimized solution to create asecond policy; and transmitting the second policy to the policyapplication pipeline; and the policy application pipeline forimplementing the second policy to the broken transaction to convert thebroken transaction to a second fixed transaction and transmit the secondfixed transaction to the network access point.
 2. The method of claim 1further comprising the network access point performing the method stepsof: transmitting the second fixed transaction to the API; and inresponse to the transmission, receiving a response from the APIindicating that the second fixed transaction has been accepted.
 3. Themethod of claim 2 further comprising the network access point, inresponse to the receipt of the response from the API indicating that thesecond fixed transaction has been accepted, transmitting an instructionto the bionic element to upload to the policy bank the set of featuresand the second policy.
 4. The method of claim 3 further comprising thebionic element uploading to the policy bank the set of features and thesecond policy.
 5. The method of claim 1 wherein the set of featuresincludes an account time stamp, a transaction type, a transactionamount, a transaction time stamp, an origin account and a destinationaccount.
 6. The method of claim 1 wherein the compliance protocolsinclude a match between a debit entry and a corresponding credit entry,an incorrect value date, and the requirement of each step beingassociated with a key generated during the step by the processingentity.
 7. The method of claim 1 wherein the network access point, priorto transmitting the first fixed transaction to the API, searches a logfile stored in a gateway cache to retrieve a communication protocolassociated with the API.
 8. The method of claim 1 wherein: the bio-meshnetwork includes a plurality of bionic elements; and the bio-meshnetwork selects the bionic element from the plurality of bionic elementsfor the processing of the broken transaction.
 9. The method of claim 1,when the bio-mesh network includes a plurality of bionic elements,further comprising a gateway cache that performs the method steps of:storing a log recording the routing of broken transactions from thenetwork access point to the plurality of bionic elements; andmaintaining a prioritization algorithm used by the network access pointto determine which bionic element in the plurality of bionic elementsshould receive an incoming broken transaction.
 10. The method of claim1, when the bionic element is a first bionic element and the brokentransaction is a first broken transaction, further comprising the firstbionic element performing the method steps of: searching a gateway cacheto determine if a second bionic element included in the bio-mesh networkis currently processing a second broken transaction having featuressimilar to features of the first broken transaction, the similaritybeing set to a pre-stored percentage similarity; putting on hold theprocessing of the first broken transaction and beginning to process athird broken transaction received from the network access point when thegateway cache stores data identifying a second broken transactioncurrently being processed that has a similarity equal to or greater thanthe pre-stored percentage similarity; and proceeding to execute theidentifying of each instance of the first transaction being processed bya processing entity when the gateway cache does not store dataidentifying a second broken transaction being currently processed withat least the pre-stored percentage similarity; wherein: the searchingthe gateway cache is performed after the policy bank fails to identify astored routine associated with the set of features and prior to thefirst bionic element executing the identifying of each instance of thetransaction being processed by a processing entity.
 11. A method foraccelerating the remediation of broken transactions using parallelmachine learning processing and optimization, the method comprising: anetwork access point receiving, from an application programminginterface (“API”), a broken transaction; the network access point forselecting a bionic element within a bio-mesh network for processing thebroken transaction and routing the broken transaction to the bionicelement; the bionic element for: receiving the broken transaction andextracting, from the broken transaction, a set of features; transmittingthe set of features to a policy bank; in response to the policy bankfailing to identify a stored routine associated with the set of featuresfor fixing the broken transaction: identifying, from a header of thebroken transaction, each instance of the transaction being processed bya processing entity; assigning to each instance, in chronological order,a step number, to represent the transaction as a sum of n_(x) steps fromx=0 to x=n; identifying, based on the information stored in the header,one or more errors in a subset of the n steps, each error including oneor more of a mismatch between a debit entry and a corresponding creditentry, an incorrect value date, and failure to be associated with a key;feed the sequence of steps, the subset of the steps, and, for each stepin the subset, the errors identified, to both a firefly algorithm (“FI”)and a genetic algorithm (“GA”); run the FI and GA, in parallel, andreceive from the FI and GA outputs including, for each step in thesubset, one or more solutions; using an optimization algorithm set tooptimize speed only, selecting from the outputs of the FI and GA, foreach step, a first optimized solution; combining each first optimizedsolution to create a first policy; transmit the first policy to a policyapplication pipeline; the policy application pipeline for implementingthe first policy to the broken transaction to convert the brokentransaction to a first fixed transaction and transmit the first fixedtransaction to the network access point; the network access point for:transmitting the first fixed transaction to the API; in response to thetransmission, receiving a response from the API indicating that thefirst fixed transaction has been rejected; transmitting a command to thebionic element to output a second policy to fix the broken transaction;the bionic element for: adjusting the optimization algorithm to optimizeboth speed and accuracy; using the adjusted optimization algorithm,selecting from the outputs of the FI and GA, for each step, a secondoptimized solution; combining each second optimized solution to create asecond policy; and transmitting the second policy to the policyapplication pipeline; the policy application pipeline for implementingthe second policy to the broken transaction to convert the brokentransaction to a second fixed transaction and transmit the second fixedtransaction to the network access point; the network access point for:transmitting the second fixed transaction to the API; in response to thetransmission, receiving a response from the API indicating that thesecond fixed transaction has been accepted; transmitting an instructionto the bionic element to upload to the policy bank the set of featuresand the second policy.
 12. The method of claim 11 wherein the set offeatures includes an account time stamp, a transaction type, atransaction amount, a transaction time stamp, an origin account and adestination account.
 13. The method of claim 11, when the bio-meshnetwork includes a plurality of bionic elements, further comprising agateway cache that performs the method steps of: storing a log recordingthe routing of broken transactions from the network access point to theplurality of bionic elements; and maintaining a prioritization algorithmused by the network access point to determine which bionic element inthe plurality of bionic elements should receive an incoming brokentransaction.
 14. The method of claim 11, when the bionic element is afirst bionic element and the broken transaction is a first brokentransaction, further comprising the first bionic element performing themethod steps of: searching a gateway cache to determine if a secondbionic element included in the bio-mesh network is currently processinga second broken transaction having features similar to features of thefirst broken transaction, the similarity being set to a pre-storedpercentage similarity; putting on hold the processing of the firstbroken transaction and beginning to process a third broken transactionreceived from the network access point when the gateway cache storesdata identifying a second broken transaction currently being processedthat has a similarity equal to or greater than the pre-stored percentagesimilarity; and proceeding to execute the identifying of each instanceof the first transaction being processed by a processing entity when thegateway cache does not store data identifying a second brokentransaction being currently processed with at least the pre-storedpercentage similarity; wherein: the searching the gateway cache isperformed after the policy bank fails to identify a stored routineassociated with the set of features and prior to the first bionicelement executing the identifying of each instance of the transactionbeing processed by a processing entity.
 15. A method for acceleratingthe remediation of broken transactions using parallel machine learningprocessing and optimization, the method comprising: a network accesspoint receiving, from an application programming interface (“API”), abroken transaction; the network access point for selecting a bionicelement within a bio-mesh network for processing the broken transactionand routing the broken transaction to the bionic element; the bionicelement for: receiving the broken transaction and extracting, from thebroken transaction, a set of features; transmitting the set of featuresto a policy bank; in response to the policy bank failing to identify astored routine associated with the set of features for fixing the brokentransaction: identifying, from a header of the broken transaction, eachinstance of the transaction being processed by a processing entity;assigning to each instance, in chronological order, a step number, torepresent the transaction as a sum of n_(x) steps from x=0 to x=n; foreach step, comparing information stored in the header associated withthe step to compliance protocols; identifying a subset of the steps thatfail to satisfy one or more of the compliance protocols; feed thesequence of steps, the subset of the steps, and, for each step in thesubset, information detailing the one or more failures to meet thecompliance protocols, to both a firefly algorithm (“FI”) and a geneticalgorithm (“GA”); run the FI and GA, in parallel, and receive from theFI and GA outputs including, for each step in the subset, one or moresolutions; combining the outputs of the FI and GA to create all possiblesolution sets, each solution set including one of the output solutionsfor each step in the subset; using an optimization algorithm, selectingfrom the solution sets the most optimal solution set, the second-mostoptimal solution set, and the third-most optimal solution step; transmitto a policy application pipeline the most optimal solution set, thesecond-most optimal solution set, and the third-most optimal solutionstep; the policy application pipeline for implementing the most optimalsolution set to the broken transaction to convert the broken transactionto a first fixed transaction and transmit the first fixed transaction tothe network access point; the network access point for: transmitting thefirst fixed transaction to the API; in response to the transmission,receiving a response from the API indicating that the first fixedtransaction has been rejected; transmitting a command to policyapplication pipeline to fix the broken transaction; the policyapplication pipeline for implementing the second-most optimal solutionset to the broken transaction to convert the broken transaction to asecond fixed transaction and transmit the second fixed transaction tothe network access point; the network access point for: transmitting thesecond fixed transaction to the API; in response to the transmission,receiving a response from the API indicating that the second fixedtransaction has been accepted; transmitting an instruction to the policyapplication pipeline to upload to the policy bank the set of featuresand the second-most optimal solution set.
 16. The method of claim 15wherein the optimization algorithm is set to optimize speed only. 17.The method of claim 15 wherein the set of features includes an accounttime stamp, a transaction type, a transaction amount, a transaction timestamp, an origin account and a destination account.
 18. The method ofclaim 15 wherein the network access point, prior to transmitting thefirst fixed transaction to the API, searches a log file stored in agateway cache to retrieve a communication protocol associated with theAPI.
 19. The method of claim 15 wherein: the bio-mesh network includes aplurality of bionic elements; and the bio-mesh network selects thebionic element from the plurality of bionic elements for the processingof the broken transaction.
 20. The method of claim 15, when the bio-meshnetwork includes a plurality of bionic elements, further comprising agateway cache that performs the method steps of: storing a log recordingthe routing of broken transactions from the network access point to theplurality of bionic elements; and maintaining a prioritization algorithmused by the network access point to determine which bionic element inthe plurality of bionic elements should receive an incoming brokentransaction.